@article{PlatzWeckmannPeketal.2022,
  author    = {Platz, Anna and Weckmann, Ute and Pek, Josef and Kovacikova, Svetlana and Klanica, Radek and Mair, Johannes and Aleid, Basel},
  title     = {3D imaging of the subsurface electrical resistivity structure in West Bohemia/Upper Palatinate covering mofettes and quaternary volcanic structures by using magnetotellurics},
  series = {Tectonophysics : international journal of geotectonics and the geology and physics of the interior of the earth},
  volume    = {833},
  journal   = {Tectonophysics : international journal of geotectonics and the geology and physics of the interior of the earth},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0040-1951},
  doi       = {10.1016/j.tecto.2022.229353},
  pages     = {20},
  year      = {2022},
  abstract  = {The region of West Bohemia and Upper Palatinate belongs to the West Bohemian Massif. The study area is situated at the junction of three different Variscan tectonic units and hosts the ENE-WSW trending Ohre Rift as well as many different fault systems. The entire region is characterized by ongoing magmatic processes in the intra-continental lithospheric mantle expressed by a series of phenomena, including e.g. the occurrence of repeated earthquake swarms and massive degassing of mantle derived CO2 in form of mineral springs and mofettes. Ongoing active tectonics is mainly manifested by Cenozoic volcanism represented by different Quaternary volcanic structures. All these phenomena make the Ohre Rift a unique target area for European intra-continental geo-scientific research. With magnetotelluric (MT) measurements we image the subsurface distribution of the electrical resistivity and map possible fluid pathways. Two-dimensional (2D) inversion results by Munoz et al. (2018) reveal a conductive channel in the vicinity of the earthquake swarm region that extends from the lower crust to the surface forming a pathway for fluids into the region of the mofettes. A second conductive channel is present in the south of their model; however, their 2D inversions allow ambiguous interpretations of this feature. Therefore, we conducted a large 3D MT field experiment extending the study area towards the south. The 3D inversion result matches well with the known geology imaging different fluid/magma reservoirs at crust-mantle depth and mapping possible fluid pathways from the reservoirs to the surface feeding known mofettes and spas. A comparison of 3D and 2D inversion results suggests that the 2D inversion results are considerably characterized by 3D and off-profile structures. In this context, the new results advocate for the swarm earthquakes being located in the resistive host rock surrounding the conductive channels; a finding in line with observations e.g. at the San Andreas Fault, California.},
  language  = {en}
}
@article{PlatzWeckmann2019,
  author    = {Platz, Anna and Weckmann, Ute},
  title     = {An automated new pre-selection tool for noisy Magnetotelluric data using the Mahalanobis distance and magnetic field constraints},
  series = {Geophysical journal international},
  volume    = {218},
  journal   = {Geophysical journal international},
  number    = {3},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0956-540X},
  doi       = {10.1093/gji/ggz197},
  pages     = {1853 -- 1872},
  year      = {2019},
  abstract  = {In Magnetotellurics (MT) natural electromagnetic field variations are recorded to study the electrical conductivity structure of the subsurface. Thereby long time-series of electromagnetic data are subdivided into smaller segments, which are Fourier transformed and typically averaged in a statistically robust manner to obtain MT transfer functions. Unfortunately, nowadays the presence of man-made electromagnetic noise sources often deteriorates a significant fraction of the recorded time-series by overprinting the desired natural field variations. Available approaches to obtain undisturbed and high quality MT results include, for example robust statistics, remote reference or multi-station analyses which aim at the removal of outliers or uncorrelated noise. However, we have observed that intermittent noise often affects a certain time span resulting in a second cluster of transfer functions in addition to the expected true MT distribution. In this paper, we present a novel criterion for the detection and pre-selection of EM noise in form of outliers or additional clusters based on a distance measure of each data segment with regard to the centre of the data distribution. For this purpose, we utilize the Mahalanobis distance (MD) which computes the distance between two multivariate points considering the covariance matrix of the data that quantifies the shape and the size of multivariate data distributions. As the MD considers the covariance matrix, it corrects not only for different variances but also for any correlation between the data. The computation of both, the mean value and covariance matrix, is susceptible to ouliers (e.g. noise) and requires a statistically robust estimation. We tested several robust estimators, for example median absolute deviation or minimum covariance determinant algorithm and finally implemented an automatic criterion using a deterministic minimum covariance determinant algorithm. We will present results using MT data from various field experiments all over the world, which illustrate successfull data improvement. This approach is able to remove scattered data points as well as to reject complete data cluster originating from noise sources. However, like all purely statistical algorithms the criterion is limited to cases where the majority of the recorded data is well-behaved, that is noise content is below 50 per cent. If the majority of data points originates from noise sources, the new criterion will fail if used in an automatic way. In these cases, additional input by the user either manually or in an automated fashion can be utilized. We therefore suggest to use an add-on criterion to back the MD selection and subsequent robust stacking in form of a physically motivated constraint based on the magnetic incidence direction. This property indicates whether the magnetic field originates from various sources in the far field or from a strong and well defined source in the near field.},
  language  = {en}
}